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What is the goal of the scientific method?
To use verifiable results to construct casual theories that explain why phenomena behave the way that they do
What are the most important components of the scientific method?
Knowledge, construction of theory, verification, falsifiability
Inductive
One draws an inference from a set of propositions and observations. Specific to general
The Scientific Method
1. Identify the problem, 2. Research Questions, 3. Theory, 4. Hypotheses, 5. Empirical analysis
What is a literature review?
Systemic examination and interpretation of the literature for the purpose of informing further work on a topic
Methods for writing a lit review
Method 1: Focus on individual references, Method 2: Focus on concepts, ideas, and methods
How to write lit review
Scientific relevance, building a theory, disagreement to the literature, and data and methods
Independent variable (in polsc)
A phenomena that will help explain political characteristics or behavior
Empiricism
Uses observation to judge the tenability of arguments
Deductive
Arguments are proven to be true through the use of several logical statements in which a conclusion is true because the underlying premise is true. General to specific.
Dependent variable (in polsc)
Thought to be caused, to depend on, or to be a function of the independent variable
What is an independent variable?
An independent variable is thought to influence, affect, or cause variation in another variable
What is a dependent variable?
A dependent variable is thought to depend upon or be caused by variation in an independent variable
Antecedent variable
A variable that occurs prior to all other variables
Intervening variable
A variable that occurs closer in time to the dependent variable
A casual relationship has three components:
1. X and Y covary, 2. the change in X precedes the change in Y, 3. covariation between X and Y is not a coincidence
Characteristics of a good hypothesis
1. Empirical v. Normative, 2. Relationship between the occurrences, 3. Plausibility, 4. State the direction of the relationship, 5. Consistent with the data, 6. Data should be feasible to obtain and would indicate if the hypothesis is defensible
A hypothesis must...
Specify a unit of analysis
Cross-level analysis
A type of analysis in which researchers use data collected for one unit of analysis to make interference about another unit of analysis
Ecological inference
To use aggregate data to study the behavior of individuals
Ecological fallacy
The use of information that shows a relationship for groups to infer that the same relationship exists for individuals when in fact there is no such relationship at the individual level
Conceptualization
the process of defining a term
Operationalization
determining how a concept will be measured, such as deciding how to record empirical observations of the occurrence of an attribute or behavior using numerals or scores.
Applied research
Research is designed to produce knowledge useful in altering a real-world condition or situation.
Empirical research
Research-based on actual, "objective" observation of phenomena.
Pure, theoretical, or recreational research
Research designed to satisfy one's intellectual curiosity about some phenomena.
Constructionism
An approach to knowledge that asserts humans actually construct- through their social interactions and cultural and historical practices- many facts they take for granted as having an independent, objective, or material reality.
Critical theory
The philosophical stance that disciplines such as political science should assess society critically and seek to improve it, not merely study it objectively.
Empiricism
Relying on observation to verify propositions.
Normative knowledge
Knowledge that is evaluative, value-laden, and concerned with prescribing what ought to be.
Nonnormative knowledge
Knowledge is concerned not with evaluation or prescription but with factual or objective determinations.
Literature review
A systemic examination and interpretation of the literature for the purpose of informing further work on a topic.
Convergent construct validity
When a measure of a concept is related to a measure of another concept with which the original concept is thought to be associated.
Dichotomous variable
A variable with only two categories- these variables are special cases as they can be used at the nominal, ordinal, or even ratio level.
Intervening variable
A variable coming between an independent variable and a dependent variable in an explanatory scheme.
Discriminant construct validity
A method of demonstrating measurement validity by comparing two measures that theoretically are expected NOT to be related.
Ordinal-level measure
Indicates that the values assigned to a variable can be compared in terms of having more or less of a particular attribute.
Interval-level measure
Includes the properties of the nominal level and the ordinal level. But unlike nominal and ordinal measures, the intervals between the categories or values assigned to the observations do have meaning.
Nominal-level measure
Indicates that the values assigned to a variable represent only different categories or classifications for that variable
Ratio-level measure
This type of measurement involves the full mathematical properties of numbers and contains the most possible information about a measured concept
Cluster sample
A probability sample is used when no list of elements exists. The sampling frame initially consists of clusters of elements.
Convenience sample
A nonprobability sample in which the selection of elements is determined by the researcher's convenience.
Disproportionate sample
A stratified sample in which elements sharing a characteristic are underrepresented or overrepresented in the sample.
Nonprobability sample
A sample for which each element in the total population has an unknown probability of being selected.
Population parameter
A characteristic or an attribute in a population (not a sample) that can be quantified.
Probability sample
A sample for which each element in the total population has a known probability of being selected.
Proportionate sample
A probability sample that draws elements from a stratified population at a rate proportional to the size of the samples.
Purposive sample
A non-probability sample in which a researcher uses discretion in selecting elements for observation.
Sample bias
The bias occurs whenever some elements of a population are systemically excluded from a sample. It is usually due to an incomplete sampling frame or a nonprobability method of selecting elements.
test-retest method
Conduct test to same observation in 2 periods
alternative form
2 different methods of measure for the same concept
split halves
2 measures of the same concept at the same time
summation index
combines the scores on multiple question to create one single measure of a concept
likert scale
uses only select questions from an index that differentiate between different respondents to create a single score for each respondent
guttman scale
determines how strongly a surveyed person holds an opinion by using a series of yes or no questions or agree or disagree statements
mokken scale
hierachical scaling method similar to guttman scale
sample
any subset of units collected in some manner from the population
population
any well-defined set of units of analysis
sample statistic
used to approxiamate the corresponding population or values
statistical inference
supportable conjecture about the unknown characteristics of a population on a sample statistic
estimator
a sample statistic based on a sample observation that estimates the numerical characteristic or parameter
sampling error
difference between a sample statistic and population parameter
sampling distribution
a theoretical frequency distribution of a statistic generated from an infinite number of samples drawn from a population
element/ unit of analysis
a single occurrence, realization, or instance of the objects or entities being studied
sampling frame
a list from which sampling units are drawn into a sample
stratum
a subgroup of a population that has one or more characteristics
snowball sample
relies on elements in the target population to identify other elements in the population for inclusion in the sample and is particularly useful when studying hard to locate or identify populations
quota sample
elements are chosen for inclusion in a non-probabilistic manner in proportion to their representation in the population
purposive or judgmental sample
study a diverse or limited number of observations, a case study